1. Field of the Invention
The present invention relates to image signal processing techniques, and in particular relates to image signal processing techniques for reducing the lens shading phenomenon on images.
2. Description of the Related Art
In optical imaging, lens shading (vignetting) is a phenomenon that reduces the brightness of an image at a periphery thereof, as compared to the center of the image. This phenomenon is usually caused by defects in lens mechanism. For example, lens shading may occur when off-axis light beams projected onto the image sensors are partially blocked by objects such as filters, secondary lenses, and lens hoods. Physically, lens shading is mainly resulted due to the differences of the ray traveling distances between the pixels in the center and those at a periphery of the image.
The lens shading phenomenon is usually an undesired effect. Thus, the image signal method, called the lens shading correction (LSC) method, is used to compensate for the effect. In general, the purpose of the lens shading correction method is to adjust the brightness of an image to satisfy the following criteria: (1) the pixels with the maximum brightness are located at or around the image center; and (2) other pixels have a brightness which is not smaller than, for example, 0.8, times that of the maximum brightness.
FIGS. 1A and 1B illustrate a Mesh Grid method of the prior art used for the lens shading correction method. In the Mesh Grid method, the whole image as shown in FIG. 1A is divided into numerous sub-areas, and each sub-area is given a gain value, such as 1.9, 1.8, 1.7 and 1.6, as shown in FIG. 1B, for tuning the brightness of the sub-areas, respectively. However, for an image having a great number of pixels, this method may require a significant amount of registers or memory units for storing the gain values and thus hardware implementation may be costly.
There is another method in the prior art for the lens shading correction method which uses a high-order polynomial for computing the gain value for each pixel of an image. The following shows an exemplary two-dimensional fourth-order polynomial Lgain used in the method, which calculates a gain value for each pixel:Lgain=A×(x−xc)4+B×(x−xc)3+C×(x−xc)2+D×(x−xc)+E×(y−yc)4+F×(y−yc)3+G×(y−yc)2+H×(y−yc)+I+C11(x−xc)3(y−yc)+C12(x−xc)2(y−yc)2+C13(x−xc)(y−yc)3C14(x−xc)2(y−yc)+C15(x−xc)(y−yc)2+C16(x−xc)(y−yc),where (x, y) represents the Cartesian coordinates of a pixel, (xc, yc) represents the center of the polynomial, and A, B, C, D, E, F, G, H, I and C1j, j=1-6 are given coefficients of the polynomial. It is noted that, although, by using this high-order polynomial, this method may produce much more accurate gain values for the pixels, calculation is quite complicated and hardware implementation is still costly.
Also, sometimes, in the prior art, a low-order polynomial is used for gain computation for the lens shading correction method. However, in many applications where the relative illumination (RI) of an image, that is, the ratio of the brightness in the corner to that of the center of the image, is lower than 30%, the method often fails to satisfy the criteria for adjusting the brightness of the image